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Grain-size sorting withinriver bars in relation to

downstream fining along awandering channel

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Citation: RICE, S.P. and CHURCH, M., 2010. Grain-size sorting within riverbars in relation to downstream fining along a wandering channel. Sedimentol-ogy, 57 (1), pp. 232 - 251.

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• This article was submitted for publication in the journal, Sedimentology[ c© The Authors. Journal compilation c© International Association of Sed-imentologists]. The definitive version is published by John Wiley & Sonsand is available at: http://dx.doi.org/10.1111/j.1365-3091.2009.01108.x

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1

Scales of variability in bed material gravels: Sorting across river

bars in relation to downstream fining

STEPHEN P. RICE1 and MICHAEL CHURCH2

1. Department of Geography, Loughborough University, Loughborough, Leicestershire, LE11

3TU, UK. (s.rice@lboro.ac.uk)*.

2. Department of Geography, The University of British Columbia, Vancouver, British

Columbia, Canada V6T 1Z2.

Submitted to Sedimentology, March, 2009

Short running title: Bar-scale sediment sorting

* corresponding author

2

ABSTRACT

The grain-size variability of riverbed gravels at bar scales is poorly understood, as are the

relations between variability at this scale and at reach and river scales. Surface and subsurface

grain size distributions were therefore examined at reach, bar and bedform scales along lower

Fraser River, British Columbia, Canada. Grain-size variations within compound bars are

conditioned by longitudinal position, elevation and morphological setting. Surface and

subsurface sediments tend to decrease in median size from bar head to bar tail by 33% and

17%, respectively. Higher elevations attract smaller particle sizes because of reduced flow

competence during high stages. Unit bars have surface sediments that are finer and better

sorted than the bed materials in bar-top channels and along the main bar edges. Secondary

unit bars tend to have a lower sand content than other features, a consequence of sediment

resorting. Individual unit bars and gravel-sheets exhibit streamwise grain-size fining and lee-

side sand deposition. Through time, morphological adjustments, even significant amounts of

cut and fill, do not ipso facto cause changes in surface grain sizes, yet sediment characteristics

can change without any significant morphological adjustment taking place. At the reach-scale

there is a clear downstream fining trend, but local variability is consistently high due to

within-bar differences that result from sorting by position, elevation and morphology. The

surface median grain size range on individual bars is, on average, 25% of that along the entire

50 km reach but is 68% on one bar. While the overall fining trend yields a downstream

change in surface median size of 0.76 mm km-1, the average value for head-to-tail size

reduction on individual bars is 6.3 mm km-1, an order of magnitude difference that highlights

the effectiveness of bar-scale sorting processes in gravel-bed rivers. We discuss possibilities

for modelling bar-scale variability and the interaction of the different controls that are

identified.

(307 words)

Keywords: compound bar, fluvial sediment, grain size, gravel sheet, unit bar, wandering

channel

3

INTRODUCTION

A large body of work has revealed how bed material grain-size varies in gravel-bed rivers at

reach and river-length scales and has sought to explain the principal spatial features, including

downstream fining (Sternberg, 1875; Church and Kellerhals, 1978) and the gravel-sand

transition (Yatsu, 1955; Sambrook Smith and Ferguson, 1995). In comparison, the variability

of river-bed grain size at bar scales has been the subject of fewer systematic measurement

programs and modelling efforts despite the casual observation that many have made, that bar-

scale sorting typically produces impressive within-bar grain size differences. Church and

Kellerhals’ (1978) analysis of replicate Wolman samples collected from 39 bar-head sites on

Peace River, British Columbia showed that within apparently homogeneous textural units on

single bars, between-sample variance was significantly greater than within-sample variance

and that this added significant scatter to downstream (between bar) fining patterns. Bar-scale

sorting and its relation to the larger-scale longitudinal trend have substantial implications for

sedimentary geology and fluvial geomorphology in terms of explaining the character of

alluvial fills and analysing controls on bed load sediment transport and channel hydraulics.

Distributed quantitative measurements have rarely been used to systematically examine grain

size across gravel bars (but see Ashworth and Ferguson, 1986; Lunt and Bridge, 2004) but

facies mapping of bar surfaces (Bluck, 1976; Forbes, 1983; Wolcott and Church, 1991),

remote sensing of bar surface texture (Carbonneau et al., 2004; Chandler et al., 2004; Verdu

et al., 2005) and measurements of grain size along transverse transects across braid bar

complexes (Mosley and Tindale, 1985; Dawson, 1988; Seal and Paola, 1995) reveal the

patchy nature of textural variation. This patchiness arises from sorting of heterogeneous

sediments by imperfectly understood mechanisms operating at various scales (Whiting, 1996;

Powell, 1998). At grain scales, segregation by size occurs at entrainment because of size-

dependent differences in inertia, protrusion (hence drag) and pivot angle, and during

deposition because of size-dependent interactions between the bedload and the underlying bed

surface texture - for example “like-seeks-like” phenomenon (Moss, 1963; Kuenen, 1966;

Clifford et al., 1993), congestion sorting (Iseya and Ikeda, 1987; Whiting et al., 1988) and

particle overpassing (Allen, 1983; Carling, 1990). At larger, bedform scales bedload is sorted

during transport because of size-dependent differences in the response of particles to gravity

effects – so called topographic sorting – (Paola, 1989; Lisle et al., 1991) and to variations in

near-bed forces induced by local flow patterns around bedforms (Brayshaw et al., 1983), in

bends and around bars (Ashworth, 1996a). The operation of processes like these at bar scales

4

may have implications for larger scale sorting at reach scales, between bars. For example, in a

sequence of alternate bars or bar-chute units, upstream trapping of relatively coarse materials

in bar heads and pools may reduce the availability of those sizes downstream, forcing reach-

scale longitudinal fining (Bluck, 1987). On compound bars the situation is further

complicated because the unit bars and unit bar remnants that are the primary elements of

bedform construction and that define an important scale at which many sorting phenomena

operate, are arranged in complex vertical and areal patterns that reflect complicated

depositional and erosional histories.

In this paper we describe and explain aspects of grain size variation across compound bars

and discuss bar-scale patterns in relation to larger-scale downstream trends. First, we examine

how bed material grain size varies with longitudinal position on the bar, with elevation of the

bed surface and with the local morphological setting. Each of these factors is implicated in

previous work as a potential cause of bar-scale variability. For example, the most widely

reported bar-scale sorting phenomenon is the tendency for bar heads to be coarse relative to

bar tails (Leopold and Wolman, 1957; Church, 1972; Bluck, 1974; Lewin, 1976; Ashworth

and Ferguson, 1986; Lunt and Bridge, 2004;) but, although head to tail sorting has been

measured on simple unit bars (Smith, 1974), there has not been any systematic quantification

of head to tail fining on compound bars. Similarly, several investigators have noted the

apparent influence of bar morphology for structuring bar-scale variations of grain size (Bluck,

1976; 1979; Lunt and Bridge, 2004) and drawn basic contrasts between channel and bar

characteristics, but there has been relatively little explicit consideration of how grain size

varies between morphological features or across the complex topography of compound bars.

Second, we examine how grain size varies across unit bar surfaces because previous evidence

is inconsistent. While Smith (1974) observed downstream fining of surface sediments on

seven simple unit bars studied on the Kicking Horse River, British Columbia, Lunt and

Bridge (2004) observed downstream coarsening of sub-armour layer sediments on unit bars of

the Sagavanirktok River, Alaska. Examples of both downstream fining (Livesey et al., 1998)

and downstream coarsening (Iseya and Ikeda, 1987) are apparent in flume studies where

sheets have been observed. Third, we consider the short-term temporal variability of bed

material grain size as compound bars are modified by unit bar accretion and erosion. Finally,

we compare our findings with the evidence for systematic downstream changes in bed

sediment texture and examine the combined effects of bar-scale sorting relative to

5

downstream fining rates. The field site is in the gravel reach of lower Fraser River, British

Columbia, Canada.

FRASER RIVER GRAVEL REACH

The gravel reach extends for approximately 50 km from Laidlaw, where the river emerges

from confinement between valleyside slopes and terraces, to Sumas Mountain, immediately

upstream from the town of Mission, where there is a rapid gravel-sand transition (Figure 1).

Through the gravel reach the river exhibits a wandering style within an active channel zone

between one and two kilometres wide that is partially constrained by flood defences. Near

Laidlaw, at the Agassiz gauge, the river is 512 m wide at mean annual flood stage, has a mean

depth of 6.6 m, a mean velocity of 2.6 m s-1 and a gradient of 4.8 x 10-4. Corresponding values

at Mission are w = 540 m, d = 12.6 m, v = 1.5 m s-1 and S = 5.0 x 10-5 (McLean et al., 1999).

Most bed load transport, deposition and reworking occur during an annual snowmelt freshet

in late spring and early summer. At Mission (Water Survey Canada, gauge 08MH024), the

mean annual flow is 3410 m3 s-1 and the mean annual flood is 9790 m3 s-1 .

Rice et al. (2009) present a morphological typology for compound bars in wandering gravel-

bed rivers that is primarily developed from observations in the gravel reach of Fraser River.

The fundamental morphological unit is the familiar pool-riffle-bar triplet (Bluck, 1976;

Lewin, 1976; Ferguson and Werrity, 1983): deposition grows a bar where flow diverges

across an oblique riffle, while scour creates a pool that is constrained by the facing bank

where flow converges below the riffle front. Several styles of bank-attached lateral or, less

frequently, medial bars are the dominant macroforms (Jackson, 1975). The scale of the river

is such that these bars may be up to 2.5 km in length and may exceed a kilometre in width.

The compound bars record vertical and lateral accretion of unit bars and their subsequent

modification by cut and fill processes in secondary channels, seasonal anabranches and

smaller bar-top channels that are progressively occupied as stage rises during flood events.

Unit bars, built by the stacking of gravelly bedload sheets, are the basic building blocks that

record individual sediment depositing episodes and dominate the process of morphological

change. The characteristic length scale varies between 101 and 103 m. Primary unit bars are

those which deliver sediment to the bar complex from the principal channel whereas

secondary unit bars are the product of dispersal of sediment from the primary accretion sites

into and through the bar complex via secondary channels, seasonal anabranches and smaller

6

bar-top channels. Figure 2 illustrates these various supraplatform features for one bar on

Fraser River (see Rice et al. (2009) for additional illustrations, particularly Figures 6, 7, and 9

therein). Analysis of bar development on decadal timescales shows that compound bar

formation is controlled by shifts in the position of the principal channel and, therefore, loci of

erosion and unit-bar deposition, but long-term histories reveal the potential for long sequences

(approaching 100 years) of persistent accretion.

METHODS

To characterise bar sediments along the gravel reach, 53 surface (Wolman) and 48 subsurface

samples were collected from nineteen compound bars between Wahleach bar near Laidlaw

and Yaalstrick bar close to Mission during the winter of 2000. To evaluate gross within-bar

variability, two or more samples were collected from sites within the upper, middle and lower

thirds of most bars. Bulk samples that met the 1% criterion of Church et al. (1987) were

collected by pooling small sub-samples from across a larger area, e.g. the bar head. Wolman

samples were positioned at a representative site within the larger unit and consisted of

approximately 400 grains collected from a 20 x 5 m grid with 0.5 m spacing.

To investigate bar-scale variability in greater detail, an additional 87 surface samples and four

subsurface samples (in this case, from single pits) were collected from Queens Bar in April

2000 (before the freshet). Samples were located in a quasi-systematic manner to cover the

entire survey area and ensure representation of the major morphological features. Wolman

samples of 360-400 grains were collected from homogeneous units at 41 sites and a photo-

count method (see below) was used at 46 sites. In September 2000 (after the freshet), 21 of

these sampling positions were reoccupied and Wolman samples were again collected. In

September 2004, 17 positions were reoccupied and sampled again, and 20 new sites were

established. On this occasion, 19 Wolman samples were collected and the AGS (automated

grain-sizing) photographic method (Graham et al., 2005a; 2005b) was employed at 18 sites.

Additional surface samples were collected from several other sites where features of interest

were surveyed, including 51 photo-count samples on Spring Bar and Gill Island during

September 2001.

During the collection of Wolman samples, templates were used to sort grains more than 8 mm

in diameter into half-psi size classes. Smaller grains were classified as 4 to 8 mm or as less

7

than 4 mm, which we define as the ‘sand’ fraction. From the Wolman samples we obtained a

percentage sand cover value and could also derive either coarse-fraction percentiles from a

distribution truncated at 4 mm or percentiles for the entire distribution including sand. Clean

and sandy gravels (those obscured by a thin, discontinuous veneer of sand) dominate the

active portions of the bed. Although the sand cover is of interest, it is sometimes of interest to

establish the size distribution of the coarser fraction without the sand component because the

sand veneer is quickly flushed away during floods and it is the gravel component that

ultimately determines the stability of the bar surface and reflects the peak entrainment stresses

at a site.

The photo-count method is based on a simple calibration between particle size and the

number of particles per unit area (Rice and Church, 1998). At 83 sites where Wolman data

were collected (on ten bars along the reach) a vertical photograph was taken of a 0.5 by 0.5 m

quadrat laid down at random within the Wolman grid. After correction for sand coverage and

obscuration by shadow, calibration relations were established between count greater than 4

mm and Wolman-derived D50 and D95 (truncated to exclude the < 4 mm sand fraction). Sites

with more than approximately 5 % exposed sand degraded the quality of the relations and

were excluded. The resulting calibrations yield prediction limits (α = 0.05) for mean D50 and

D95 estimates of ±5 and ±17 mm respectively, and were used to estimate coarse grain

percentiles at 38 sites where only photographs were collected (estimates were not obtained at

8 of the original 46 sites where sand cover was greater than 5%). The AGS method employed

in 2004 uses robust image processing tools to automatically identify and measure surface

grain sizes. Wolman samples were collected at eleven sites and provide a check on the

method’s application on Fraser River. Comparison of Wolman with AGS D50 and D95

estimates revealed no significant bias and root mean square differences of ±3 mm and ±9 mm,

respectively.

In addition to grain size information, bed structure was described using the “loose”,

“underloose”, “normally loose” classification suggested by Church (1978) and the degree of

embeddedness and strength of imbrication were evaluated qualitatively. Finally, high-stage

flow direction was estimated by measuring the orientation of imbricated clasts. Ten

measurements were made at each sediment sampling site.

8

OBSERVATIONS

Down-Bar position and grain size

During sampling in 2000, at least one surface sample was collected from the upstream and

downstream thirds of nine bars, and at least one subsurface sample from the upstream and

downstream thirds of fourteen bars along the reach (in a population of 20 bars). For these

cases, the ratio of upstream to downstream median grain sizes (untruncated samples) was

calculated as Δ50 = D50U / D50D, where the subscripts U and D refer to upstream and

downstream positions respectively. In eight of the nine surface cases and ten of the fourteen

subsurface cases, Δ50 > 1.0 indicating that bed material size tends to be coarser in the

upstream thirds of compound bars than in the downstream thirds. Mean surface and

subsurface Δ50 values are 1.47 and 1.19 respectively, indicating 33% and 17% decreases in

median size from bar head to bar tail. This bar-scale longitudinal differentiation decreases

with distance downstream (Figure 3) presumably because of an overall improvement in bed

material sorting due to downstream fining.

Surface elevation and grain size

Across Queens Bar, sites at higher elevations are associated with smaller maximum particle

sizes (Figure 4), presumably because water depth at high-stage and, therefore, maximum

shear stress decline as elevation increases. General competence considerations suggest that

maximum grain size should be related to water depth by

s

SYDγτ ⋅

= *max (1)

where Dmax is maximum particle size, Y is water depth, S is the energy slope, γs is submerged

specific weight (=1.65) and τ* is Shields’ dimensionless critical shear stress (≈ 0.03 for dis-

entrainment). The D95 values plotted in Figure 4 are for 87 surface samples collected along

the flank and through the main anabranches of Queens bar in April 2000. During moderate

discharge at that time, average water surface slope across the sampled area was 0.0004

yielding a first approximation of Dmax / Y = 0.008 (m m-1), the rate at which maximum grain

size should increase as water depth increases. When expressed in terms of the decrease in

grain size per unit increase in bed surface elevation, the appropriate slope is –0.008. The bulk

of the data plotted in Figure 4 is neatly contained by an envelope curve with this slope,

9

supporting the argument that variations in particle size with elevation are caused by

differences in imposed shear stresses.

Morphological setting and grain size

The 87 surface samples from Queens bar were classified according to their site morphology as

primary unit bars, secondary unit bars, bar-top channels and principal channel edge. The

surface sediment characteristics of each group are reported in Table 1a. Although individual

sites in different categories share common surface characteristics, sorting processes do

produce some significant between-group differences. Primary and secondary unit bars have

mean D50 and D95 values that are very similar and significantly finer than those for the bed

materials in bar-top channels and along the main bar edge (t-tests, p < 0.001; Figure 5A). Unit

bar gravels are marginally better sorted and the difference in sorting between primary unit

bars and erosional bar edges is significant (Mann-Whitney U test, p = 0.033). These basic

distinctions are explained by the greater mobility and simple depositional history of the unit

bar sediments and their higher elevations (t-tests, p < 0.001; Figure 5B), and therefore lower

entrainment stresses at high stage. Some sites on the unit bars were ‘over-loose’ and the

majority of sites were ‘normally’ loose (Table 1a). In contrast, ‘under-loose’ sediments

dominated the bar-top channels (62%) and no sites were classed as ‘over-loose’. This reflects

the relative mobility and ephemeral flow across unit bars in contrast to the structural

consolidation achieved by longer-lived competent flows in the surrounding channels.

Secondary unit bars were the only setting where surface censoring was observed, typically at

those sites close to the edge of a leading avalanche face. This presumably reflects the

development of a steep energy gradient and, therefore, strong hydraulic winnowing of matrix

fines across the avalanche face as stage falls.

Average percentage sand is significantly lower on secondary unit bars than in the other three

settings (Mann-Whitney U tests, p < 0.001), each of which exhibits a wide range of sand

cover from zero to over 48 % (Table 1a). While 67 % of secondary unit bar sites had ‘clean’

surfaces and none were ‘heavily’ embedded, in bar-top channels only 17 % were ‘clean’ and

48 % were ‘heavily’ embedded. The high proportion of sand in bar-top channels is caused by

proximal disconnection as stage falls. Fines settle out of suspension or stall as they move

along the bed to partially or completely veneer the gravel surface with sand and then silt. At

distal locations, where connections to the principal or secondary channel are maintained for

long periods so that sediment laden waters are refreshed, these veneers may be several

10

centimetres thick. In contrast, the low proportion of sand on secondary unit bar surfaces

reflects the high relative position of their surfaces, which means that they are less likely to be

inundated by deep, slack water from which a significant amount of fine sediment can be

deposited. High proportions of sand at some sites on primary unit bars reflect local hydraulic

conditions. For example where a unit is being overridden by a fresh bar the surface of the

lower, older unit is prone to fine sedimentation in the lee of the advancing avalanche face.

Single subsurface samples collected from each type of morphological setting on Queens bar

show that subsurface grain-size characteristics also vary between morphological settings

within bars. These samples provide good evidence that the degree of variability in subsurface

sediment characteristics is similar to that of the corresponding surface sediments (Figure 6A)

and, therefore, that the sorting processes that produce diverse surface textures affect the

associated bulk deposits too. Again, a primary distinction can be drawn between the

characteristics of unit bar and channel samples. Samples from the two unit bars yielded

similar grain-size distributions that were deficient in coarse gravels and cobbles relative to the

bar-top and bar-edge channel samples (Table 1b; Figure 6B). Armour ratios (= surface

D50/subsurface D50) were calculated for these four sites using untruncated surface and

subsurface GSDs. Values are low for the unit bars (= 1.3 in both cases) which reflects their

mobility and ephemeral flow regime. In contrast, the bar-edge site has an armour ratio

approaching 3.0, which reflects surface winnowing of fine sediment and is consistent with the

greater structural consolidation of channel surfaces noted above. The bar-top channel site has

a low armour ratio (< 1) because the surface at the sampling location was heavily embedded.

This is common (14 of 29 bar-top channel sites were heavily embedded) and reflects the

propensity for fine sedimentation from still water or slackening flows as bar-top channels are

isolated from the principle and secondary channels by falling stage during the receding limb

of the freshet.

A further source of variability is the degree of bimodality in the subsurface sediments. Each

of the bulk grain size distributions is bimodal with a gap in the 0.5 mm to 5.0 mm range.

However, bimodality is notably stronger in the two unit bar sediments and is weakest in the

bar edge sample (Figure 6B). This suggests that bimodality is preferentially generated by

active transport and deposition or preferentially restricted in high-energy erosive

environments where sand fractions are more mobile.

11

Grain-size variations across sheets and unit bars

Grain size variations across individual unit bars and the gravel-sheets which build them tend

to exhibit streamwise grain-size fining and lee-side sand deposition (Figure 7). On Spring bar,

bar-head unit-bar accretion occurs across the full channel width under a relatively simple flow

field that is uncomplicated by islands or channel anabranches. Numerous gravel sheets and

stalled unit bars are evident on the bar platform. At each of seven sheet fronts, four

photographic grain-size samples were obtained, two upstream of the crest and two

downstream on the lower, partly over-ridden unit in front. All samples were collected within

10 m of the sheet crests which were, on average, 0.11 m high. Sand cover was greater

downstream in six of the seven cases and, on average, there was 5.8 times more sand area on

the surface downstream than upstream. This lee-side sand cover is discontinuous but reached

33% in one case (Figure 7A). Beneath the sand, the lee-side gravels tend to be coarser than in

the advancing sheet and in all seven cases, gravel sizes on the crest were finer than those

downstream (Figure 7B and C). On average, the ratio of upstream to downstream D50 was

0.70 (range, 0.49 to 0.93). The relatively coarse bed material in the lee of each advancing unit

belongs to the tail of the underlying sheet so that the differences in gravel size across each

crest suggest that there is a streamwise decrease in framework grain size toward the sheet

crest (Figure 7D). It appears that, on Spring bar, streamwise sorting occurs within each

individual sheet as it climbs up onto the back of the underlying unit. Similar streamwise

fining is apparent on the surface of flat-topped unit bars, for example flank bars on Gill Island

where D50 declines from 46 mm to 28 mm in 130 m. Fining is not ubiquitous and where the

flow field is complex grain size variations across unit bars are less consistent. Figure 7E

shows D95 values across two unit bars that were deposited on Queens during the 2002 freshet.

Along high-flow paths indicated by clast orientation, gravels more often fine downstream

(e.g. X to X’) but streamwise coarsening is sometimes apparent (e.g. Y to Y’).

The tendency for streamwise fining is consistent with some previous flume observations

(Livesey et al., 1998) but inconsistent with the observations of Whiting et al. (1988) on Duck

Creek, where gravel sheets had a relatively coarse leading edge. The material in motion on

Duck Creek is much finer than that on Fraser River (D50 ≈ 5 mm) and laboratory observations

have demonstrated the importance of a high sand content for the leading-edge congestion and

over-passing process that is associated with this type of sheet migration (Iseya and Ikeda,

1987; Dietrich et al., 1989). Fining on the Fraser River unit bars might simply reflect the

dominance of size-selective sorting where the bed load grain-size distribution is generally

12

more coarse with less sand content and where the relief of the unit bars and sheets is greater

such that depth and therefore competence vary significantly along the streamwise axis. That

is, the streamwise fining reflects the increasing downstream height of sheets that are climbing

onto existing bars.

Morphological development and temporal grain size changes

The emplacement of individual unit bars can be responsible for significant local changes of

grain size (Figure 8). For example, the flank unit bar that formed the bar edge at Calamity

before the 2002 freshet had a mean surface D50 of 32 mm (n = 9). The overriding unit that

became attached during the 2002 freshet consisted of coarser gravels with an average D50 of

44 mm (n = 5), a significant difference (t-test, α = 0.01). Despite such spectacular local events

and the general associations between morphological elements and grain size, analyses of bed

material samples from Queens bar suggest that local grain size modification can also occur in

the absence of topographic change and that topographic change does not necessarily produce

changes in grain size.

In September 2000, grain size samples were collected at 21 positions on Queens bar that had

previously been sampled in April. The freshet that occurred during the intervening period

(maximum daily discharge = 8470 m3 s-1, less than the mean annual flood) caused small-scale

reworking of bar morphology (Rice et al., 2009). Topographic surveys indicate that eight of

the sampled positions had experienced either a significant change in elevation or are likely to

have experienced the passage of a large unit bar. The remaining 13 positions underwent no

significant morphological change and were unlikely to have been affected by the passage of

unit bars. Seven of the same positions were reoccupied in September 2004 and all sites had

undergone significant changes during large-scale modification of the bar in the 2002 freshet

(maximum daily discharge = 11 000 m3 s-1, the fifth largest in the 40-year measured record).

Replicate Wolman samples yield a 95% confidence interval on D50 estimates of ±1.8 mm.

Figure 9 plots D50 for the surveys before and after the 2000 freshet (April and September

2000) and before and after the 2002 freshet (September 2000 and September 2004). The solid

lines indicate the region within which differences could be due to sampling imprecision

(±2.55 mm = √(1.82 +1.82)). It is clear that that there is a good deal of temporal consistency

such that sites are characterised by similar D50 grain-sizes before and after each flood. It is

somewhat surprising in Figure 9A, that there is not a clearer distinction between sites

13

experiencing significant cut and fill or the passage of unit bars and those where no

morphological adjustment was apparent.

On the one hand this suggests that morphological adjustments, even significant amounts of

cut and fill, do not ipso facto cause changes in surface grain sizes and, on the other hand, that

sediment characteristics can change without any significant morphological adjustment taking

place. The former may reflect the relatively well-sorted nature of the sediments on this part of

the river, such that local sorting during cut and fill can produce only small changes in median

size (which is in any case a relatively insensitive measure of change). The latter may indicate

that the magnitude of grain size change due to deep incision or burial beneath active gravel

sheets is no greater than that which can be accomplished in the surface layer by, for example,

winnowing or the discontinuous diffusion of mobile materials.

The limited changes that took place at particular locations on Queens bar are consistent with

the similarity of average bar-scale grain-size characteristics during the study period. When the

mean and variance of the 79, 21 and 17 D50 values obtained on Queens in April 2000,

September 2000 and September 2004 were compared, there were no significant differences

(F- and t-tests, α > 0.10).

The downstream trend

The dominant large-scale trend in many alluvial rivers is downstream fining caused by sorting

and abrasion processes (Russell, 1939; Parker, 1991; Ferguson et al., 1996; Rice, 1999; Lewin

and Brewer, 2002), punctuated by positive grain-size steps at coarse-sediment recruitment

points such as some tributaries (Sternberg, 1875; Miller, 1958; Knighton, 1980; Rice and

Church, 1998). This model may be disrupted to varying degrees by low sediment supply

(Singer, 2008), diffuse lateral sediment sources (Heller et al., 2001; Davey and Lapointe,

2007) and local factors that include hillslope-channel coupling (Rice and Church, 1996),

anthropogenic channel modifications (Surian, 2002) and variations in gravel mobility due to

lithological control of channel morphology (Constantine et al., 2003).

Overall downstream fining is present along the gravel reach of Fraser River, beyond which

there is a transition to sand. In 2000, multiple samples were collected from homogenous

patches on twenty individual bars. Surface D50 declined from approximately 50 to 20 mm

(Figure 10) along the gravel reach, and D90 declined from approximately 100 to 30 mm.

Corresponding values for subsurface sediments were 25 to 10 mm and 90 to 30 mm. Despite

14

these general trends, local variability is consistently high (on the order of 1 to 1.5 psi units or

log2 cycles) and, in common with many published downstream fining datasets, scatter is a

dominant characteristic. It is clear from Figure 10A, where data for individual bars are

differentiated, that much of this scatter is due to within-bar variability rather than between-bar

differences. Indeed, both surface and subsurface sediments can exhibit almost as much

variation within the limits of an individual compound bar as does the entire gravel reach. For

the nine bars where head and tail Wolman samples are available, and where we might

therefore presume to have captured a reasonable amount of the bar-scale textural variability,

the average surface D50 range is 20 mm, the maximum is 51 mm (Wahleach Bar) and the

minimum is 4 mm (Carey Bar). These contrast with the surface D50 range of 90-15 = 75 mm

for the entire set of gravel bars along the 50 km reach. This indicates that the grain size range

on individual bars is, on average, approximately 25% of the overall range in the reach but can

be as high as 68%.

An alternative expression of this pattern takes into account the distance over which sorting is

apparent at reach and bar scales. For the entire reach, the linear least-squares downstream

fining model yields a diminution rate of 0.76 mm km-1. For the nine bars with head and tail

samples (excluding the one bar where the bar tail was coarser) the rate of decline in median

grain size from head to tail ranges between 0.56 mm km-1 at Yaalstrick and 15.08 mm km-1 at

Gill, with an average of 6.31 mm km-1.

To examine temporal stability of the downstream fining trend, grain-size data from 2000 can

be compared with an earlier data set of bar-head samples collected in 1983/84 (n = 53).

Surface (Wolman) samples collected in the earlier program were only 100 clasts in size, but

that is sufficient to return a reliable estimate of the median grain size (Rice and Church,

1996). The comparison of surface materials indicates that bed materials have become finer in

the sub-reach common to both sampling programmes (between river km 108 and 140). Over

that period, mean surface D50 in the sub-reach appears to have declined significantly from 35

to 29 mm (t-test, p= 0.05). Overall fining trends remain consistent, however, with no

significant difference in the regression slopes for linear fining models for the two years

(Ancova, p = 0.83; Figure 10B). There is a possibility that differences between the two

sampling programs in sample protocol with respect to the finest grains may have induced the

result. However, reach-scale changes are presumably dominated by patterns of sediment

15

supply and transport capacity; a long run of below normal freshets between the two sampling

dates may very well have effected such a change.

Combined effects

The question arises whether the sedimentological effects described above act in combination

to affect grain size. Because downstream fining effects impose a systematic difference in

expected mean grain size from bar to bar, we ask whether the bar-scale variations we have

studied may affect that trend locally. Down-bar fining – also a systematic spatial effect –

needs to be averaged away in a representative way in order to study downstream fining from

bar to bar, while grain size variations associated with morphological setting, which vary

spatially within bars, also needs to be averaged. We also know that surface elevation affects

sediment size within bars and we do know bar platform elevation (see Church and Rice, in

review), that is, the elevation of the gravel surface above the main channel bed. Hence, using

the spatially averaged mean grain size for each bar, we may ask whether bar platform

elevation explains any of the substantial scatter of data about the mean downstream trend. We

examine this question by computing the downstream trend for data averaged across individual

bars and then examining the correlation between bar platform elevation and the residuals from

that trend. Surface and subsurface data of 12 bars are available for analysis.

Some results are displayed in Figure 11. To compute the trend line, data of Foster Bar were

excluded. Foster Bar presents a large anomaly, a circumstance that probably is related to a

large gravel extraction that occurred on the bar 4 years before sampling. The residuals do

correlate with bar thickness, except that Big Bar again presents a significant anomaly. Big Bar

is a relatively recently established bar (45 years) that has formed on top of a long diagonal

riffle in the river. The bar tail sits astride the riffle and there is a large, perennially flowing

chute channel below the riffle. With this morphology, there is little bar tail deposition of finer

sediments, which serves to elevate the mean grain size for the bar. For the remaining bars the

correlation of the residuals with bar thickness is significant (p = 0.06; for exploratory

purposes we adopt α = 0.10 as the threshold for a significant result). We tentatively conclude

that bar thickness influences grain size downstream and helps to explain residual scatter about

the reach-scale fining trend. The results displayed in Figure 11 are for surface D50. Variance

reduction in the same analysis is marginally superior for surface D90 and the pattern is

identical, but no significant effect was found for subsurface sediments.

16

Given this effect and the general expectation that bars thicken as they grow, the further

question arises whether bar age is correlated with grain size (in the absence of the fining trend

and other local effects). We know the ages of the bars, but we found that bar age did not

correlate with the residual variance from the downstream fining trend line and conclude that

there is no age effect. This is explained by the observation that once established, bars rapidly

assume a surface elevation that is close to the final elevation (Church and Rice, in review)

such that bar thickness is essentially independent of bar age.

DISCUSSION

We have demonstrated grain size variations in a gravel-bed river at scales varying from

individual sedimentary units (unit bars) within bar, through the dominant bar scale, to whole

reach scale. Within sedimentary units, size gradation is associated with distance along a

flowline and with elevation, themselves correlated so that fining occurs upward and

downstream. Overall, fining is associated with flow divergence and sediment depositional

gradient. Secondary sorting in bar top channels and resedimented units complicates the local

pattern of grain size variation so that a somewhat palimpsestic pattern of repeated local fining

gradients occurs on a compound bar.

An overall pattern of down-bar fining at the bar scale is the strongest individual gradient at

any scale. This gradient is the consequence of sediment sorting associated with steering of the

river current by the developing barform. The major sediment body dominantly grows laterally

(Rice et al., 2009; Figure 8, herein), so the lee-side regions become shadow zones into which

sediment moves over the bar-top, primarily through bar-top channels, or diffuses laterally

from the displaced main current. Predominantly finer sediment is deposited in this shadow

zone. While this bar-scale gradient is strongest, clearly demonstrating that sorting on

individual gravel bars is highly effective, this remains the aspect of bar-scale sedimentation

that is perhaps least well understood in its details.

This explanation has an affinity with Ashworth’s model of bar formation in braided rivers in

terms of the focus on mobile units and their different local transport pathways and sinks

(Ashworth et al. 1992a,b; Ashworth, 1996). In that model, the relatively small impact of

secondary flows on coarse bedload and flow divergence at emergent bar heads is thought to

lead to the concentration of relatively coarse material there, while finer sediments moved

17

laterally by secondary currents are thought to be more easily deflected around bar heads into

distributary channels, where topographic sorting promotes bar-tail deposition. Bluck (1976;

1979) emphasised the stage dependence of depositional positions across a bar platform,

suggesting that coarser bar heads are formed at high stages and finer tails in the lee of these

deposits during falling stages. Thick sandy facies are commonly deposited on Fraser River bar

tails during the receding limb of the annual hydrograph so this process is probably part of the

explanation too. It is unlikely that bar-scale fining reflects the operation of a “turbulence

template” whereby relatively coarse bar head materials generate hydrodynamics that only

relatively coarse bedload grains can tolerate, such that incoming finer grains are rejected and

transported to downstream positions (Bluck,1987; Clifford et al. 1993), because such a

process does not operate at the kilometre scale of the compound bars.

Local sorting across bars and individual bedforms produces grain size variations at the scale

of the channel width that are equivalent to those observed longitudinally over much greater

distances. In practice, this means that downstream fining patterns are revealed most clearly

when sediment variability at a local scale is minimised, usually by limiting sampling to a

particular bar-scale unit (typically the bar head) or by lumping together observations to

provide a spatial average. The usefulness of downstream fining models for prediction is then

limited to reach scale applications, while predictions of bar-scale variability require an

additional term to express the local grain-size range that can be anticipated.

Our analysis of Fraser River sediments suggests two potential means of providing such an

expression. First there is, on average, a 33% reduction in median surface grain size between

bar-head and bar-tail (defined as the upper and lower third of the compound bar surface,

respectively). Bar-scale variability on this river might be approximated by reducing a

prediction of bar-head grain size (D50U) from a downstream fining model by a proportion P (=

0.33 on Fraser River) to estimate the bar-tail grain size and thence the bar-scale range = D50U

(1– P). This simple model and the value of P requires further investigation because other

rivers are likely to exhibit different ratios; for example, the maximum particle size delivered

to bar heads presumably limits the possible magnitude of downstream bar change because the

lower limit is essentially fixed. Indeed, this example suggests a second means of estimating

bar-scale variability that relies on the possibility that the value of P may vary systematically

along a fining trend. We note that along the reach-scale fining sequence, there is a weak

decline in within-bar (between-patch) variability (R2 = 0.55 for the relation between distance

18

downstream and within-bar D50 range; Figure 10A), suggesting that patch textures become

less diverse as a systematic function of position along a fining trend. This is consistent with

the progressive downstream exclusion of coarse grains during downstream fining, leaving

available a reduced mixture of sizes for bar-scale sorting (cf. Bluck, 1987). We hesitate to

define the nature of this relation here, but a larger data set designed to establish within-bar,

between-patch variability along a number of fining sequences, may yield useful empirical

models.

At bar scales, however, there is no equivalent means of modelling textural change through

time, even though such information is important for understanding the details of alluvial

stratigraphy and the impact of river change on lotic habitats. Developing a better spatial and

temporal understanding of textural variability at even finer sub-width scales is also important,

for example, for validating and calibrating 2-D models of channel hydraulics, sediment

transport and patchy lotic habitats. Repeated plane table mapping and sediment-size analysis

of bars on the River Tulla, Scotland by Bluck (1987) revealed that most bars coarsen as they

age, which Bluck suggested was due to in situ modification by the turbulence template

mechanism (Clifford et al., 1993). We do not have a sufficiently long data set to test these

ideas, but our examination of grain size responses to mobile bed events across Queens Bar,

does show that morphological change may or may not cause local grain size changes and that

morphological stability may or may not be associated with grain size change. Moreover, we

found no correlation between bar age and residuals from the downstream fining trend.

CONCLUSIONS

We have demonstrated that sediment grain sizes found on bar surfaces in a 50-km gravel bed

reach of a large wandering gravel-bed river vary systematically with down-bar position, with

morphological setting, and with bar surface elevation. In addition, sediment texture can be

modified by secondary resedimentation on a bar but, on the bars found in this large river,

representative grain size does not necessarily change systematically, at a particular position,

over a period of years that includes repeated seasonal inundation.

The qualitatively well-known down-bar variation is by far the greatest source of variation,

quantitatively larger locally than the overall downstream fining of fluvial gravels. On lower

Fraser River, the difference amounts to an order of magnitude (6.3 mm km-1 vs. 0.76 mm km-

19

1). Its occurrence is mediated by the mutual effect of bar growth and river current steering,

which determines the developing pattern of sedimentation. Local variation in grain size due to

the surface elevation of the bar surface above the main channel bed contributes to the

observed variance in overall downstream fining.

This finding carries important implications for representative sampling of fluvial bed material

grain size along gravel-bed rivers and for both the calibration of 2-D morphodynamic models

and the interpretation of bed material grain size predicted by those models. High bar-scale

variability means that large-scale trends can only be revealed when local-scale variability is

removed; for example, by consistently sampling from a single depositional environment, like

bar-heads. While this is well-established practise amongst most geomorphologists and

sedimentologists dealing with modern sediments, it is clearly difficult to achieve when

examining limited exposures in alluvial fills or lithified gravels. High local variability also

means that single bed material samples cannot be representative of the grain sizes apparent on

a bar or across a channel width. This is problematic when trying to establish grain roughness

parameters in morphodynamic models of gravel-bed rivers and when comparing model

predictions of bed material grain size with field data (e.g., Ferguson and Church, in review).

Notwithstanding the explanations of bar-scale variability described herein, it is clear that the

complexity of sediment sorting across compound bars will continue to hinder the

identification of simple predictive models of bar-scale grain-size. In this context, empirical

information remains important, both for improving understanding of bar-scale sedimentation

and for providing calibration and test data for morphodyamic models. Recent technical

advances in distributed measurement tools (Carbonneau et al., 2005; Graham et al., 2005b;

Verdu et al., 2005) will improve our ability to document the spatial and temporal variability

of river bed sediments at bar and reach scales. Both automated airborne and ground-based

image-analysis systems now make it feasible to collect high-resolution grain size information

over large areas and, where long-term archives of air photography are available, to unlock

histories of grain-size change

Acknowledgments

Work on lower Fraser River is supported by the Natural Sciences and Engineering Research

Council of Canada through a Discovery Grant to M.Church. A host of assistants and

20

colleagues made major contributions in the field and laboratory, including Jim Chandler,

Erica Ellis, Nick Manklow, Laura Rempel, Hamish Weatherley and André Zimmermann. The

1984 sediment data were collected by David McLean.

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25

Table 1. (a) Surface and (b) subsurface sediment characteristics of morphological units on

Queens bar.

Primary unit bars

Secondary unit bars

Bar-top channels

Erosional bar edge

a) Surface layer

Number of samples1 21 [19, 9] 30 [29, 14] 29 [24, 12] 7 [7, 6]

Sand (%) 6 (0-75) 1 (0-16) 17 (0-79) 9 (0-48)

Coarse-fraction2 D50 (mm) 25 (18-30) 26 (18-32) 34 (27-34) 35 (22-43)

Coarse-fraction D95 (mm) 59 (43-72) 60 (41-76) 79 (61-99) 81 (54-97)

Sorting of coarse fraction3 0.72 (0.58-0.86)

0.76 (0.62-1.00)

0.81 (0.64-1.10)

0.89 (0.56-1.02)

Structure: overloose, normal, underloose

4, 12, 5 4, 17, 9 0, 11, 18 0, 4, 3

Embeddedness: clean, slight, moderate, heavy

8, 5, 6, 2 20, 7, 3, 0 5, 10, 0, 14 0, 3, 2, 2

Imbrication: none, weak, strong, very strong

1, 9, 9, 2 1, 10, 14, 5 0, 11, 12, 6 0, 3, 3, 1

Censored surface layers?

none 5 sites none none

b) Subsurface bulk

Number of samples 1 1 1 1

Sand (%) 18 13 21 27

D50 (mm) 19 20 23 13

D95 (mm) 63 62 78 71

Armour ratio4 1.3 1.3 0.2 2.9

Entries for surface D50, D95, sorting and percentage sand are group means with minimum and maximum values in parentheses. (1) Sample size refers to the total number of samples in each group. Sorting values were calculated only for grain size distributions based on Wolman sampling and eight photographic samples that contained more than 5% sand were not used to estimate gravel D50 and D95. Values in square parentheses therefore indicate the group sizes for gravel percentile and sorting calculations, respectively. (2) Coarse-fraction refers to grain-size distributions truncated at 4mm. (3) sorting was calculated as (Ψ84 – Ψ16)/2 (Inman, 1952). Armour ratios are for the four individual sites where subsurface data are available and were calculated using corresponding untruncated surface and subsurface GSDs.

26

Figure captions:

Figure 1. Fraser River gravel reach between Laidlaw and Mission, British Columbia,

Canada. River kilometres are measured from Sand Heads (mouth of the river); the

major bars are named.

Figure 2. Supraplatform features of a large lateral compound bar (Wellington Bar) on

Fraser River.

Figure 3. Ratio of median grain sizes (no truncation) in the upstream third to downstream

third of individual lower Fraser River bars plotted against distance downstream

(measured from river km 155). Filled circles represent surface bed materials and

open circles represent subsurface materials. Points above the dashed line are those

where coarser bed materials are found toward the bar head.

Figure 4. D95 of the coarse fraction (> 4 mm) of the surface grain size distribution plotted

against site elevation for 87 samples from Queens bar. The dashed line, which has

a slope of –0.008 is an appropriate envelope that constrains the relation between

particle size and elevation for the local channel slope (see text for details).

Figure 5. Distributions of (A) coarse-fraction (> 4mm) D95 and (B) site elevation grouped

by site morphology. Queens bar sites, details in Table 1.

Figure 6. (A) Truncated (> 4 mm) subsurface grain-size distributions compared with the

surface grain-size distributions (> 4mm truncation) at the same four sites on

Queens bar. (B) Full subsurface grain-size distributions of samples collected from

each morphological setting on Queens bar.

Figure 7. Grain-size variations across unit bars and sheets: (A) discontinuous sand

deposition in the lee of a sheet crest on Spring Bar; (B) and (C) gravel bed

materials upstream and downstream of a sheet crest on Spring bar – quadrat is

0.50 by 0.50 m; (D) tail to crest fining of bed material across a series of climbing

sheets on Spring bar – circles represent coarse-fraction (> 4mm) D50 and the

locations of photographs B and C are indicated; (E) coarse-fraction (> 4mm) D95

variations and high-flow current directions across two unit bars on Queens –

dashed lines indicate avalanche faces and symbol ‘handles’ point downstream.

27

Figure 8. Flank unit bar accretion on Calamity Bar during the 2002 freshet. Total station

surveys of (A) March 2002 and (B) April 2003. Arrows indicate flow direction in

the principle channel. Colours indicate bed elevation from low in deep blue

through brown, yellow and white to green at the highest elevations.

Figure 9 Median grain size changes at reoccupied sampling positions on Queens bar

between (A) April and September 2000 and (B) September 2000 and September

2004. Sites where there was net aggradation or erosion or that are likely to have

experienced the passage of a significant sediment unit (closed circles) are

differentiated from sites where there was no morphological change (open circles).

The diagonal lines define a zone within which differences may be due to sampling

error (see text for details).

Figure 10. (A) Median surface grain size (no truncation) plotted against distance downstream

(measured from river km 155) for the entire gravel-bed reach of lower Fraser

River. Data of individual bars are indicated by the different symbols. The majority

of scatter within the general downstream fining trend is caused by within-bar

variability. Within-bar variability (between homogeneous patches) declines

downstream. (B) Median surface grain size (no truncation) plotted against

distance downstream (measured from river km 155) for the sub-reach common to

sampling programmes conducted in 2000 and 1983/84 (between river km 108 and

140). There has been some general fining, but slopes in the linear regression

models are not significantly different (Ancova, p =0.83).

Figure 11. Departures from the downstream trend correlated with bar thickness. See text for

explanations concerning the two named, anomalous bars.

28

Figure 1

29

Figure 2

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Figure 3

31

Figure 4

32

Figure 5

33

34

Figure 7

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Figure 8

36

Figure 9

37

Figure 10

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Figure 11